Genome-wide scan for bovine twinning rate QTL using linkage disequilibrium

Twinning is a complex trait with negative impacts on health and reproduction, which cause economic loss in dairy production. Several twinning rate quantitative trait loci (QTL) have been detected in previous studies, but confidence intervals for QTL location are broad and many QTL are unreplicated. To identify genomic regions or genes associated with twinning rate, QTL analysis based on linkage combined with linkage disequilibrium (LLD) and individual marker associations was conducted across the genome using high-throughput single nucleotide polymorphism (SNP) genotypes. A total of 9919 SNP markers were genotyped with 200 sires and sons in 19 half-sib North American Holstein dairy cattle families. After SNPs were genotyped, informative markers were selected for genome-wide association tests and QTL searches. Evidence for twinning rate QTL was found throughout the genome. Thirteen markers significantly associated with twinning rate were detected on chromosomes 2, 5 and 14 ( P  < 2.3 × 10⁻⁵). Twenty-six regions on fourteen chromosomes were identified by LLD analysis at P  < 0.0007. Seven previously reported ovulation or twinning rate QTL were supported by results of single marker association or LLD analyses. Single marker association analysis and LLD mapping were complementary tools for the identification of putative QTL in this genome scan.     

Validation of SNP associations with bovine ovulation and twinning rate

Previous work identified SNP associations with twinning rate in the US Holstein population and developed a model for genomic prediction. The current study was conducted to assess the association of these SNPs with twinning rate and ovulation rate in a genetically diverse, outbred population selected for twinning and ovulation rate. A total of 18 SNPs that were components of a prediction equation for twinning rate in Holstein cattle were genotyped on 731 animals from the USDA Meat Animal Research Center production efficiency or twinning population. These 731 individuals were sires and dams well represented in the pedigrees of animals from the twinner population, and their genotypes were used in predicting genotypes for animals in the larger population (n = 16 035). Twinning rate and ovulation rate were analyzed in a two‐trait repeated records analysis with marker associations analyzed individually as fixed effects. Criteria for marker validation were effect estimate with a sign consistent with previous estimates and significance at a nominal P < 0.01. Of the 14 SNPs passing quality control assessments, only one was validated. A SNP in the 5′ flanking region of the IGF1 gene, discovered previously in a positional candidate gene analysis, was significantly associated with twinning rate in the USDA twinning population (P < 0.0002). This SNP may have utility in genomic prediction of twinning rate beyond the Holstein population.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Genome Wide Analysis of Fertility and Production Traits in Italian Holstein Cattle

A genome wide scan was performed on a total of 2093 Italian Holstein proven bulls genotyped with 50K single nucleotide polymorphisms (SNPs), with the objective of identifying loci associated with fertility related traits and to test their effects on milk production traits. The analysis was carried out using estimated breeding values for the aggregate fertility index and for each trait contributing to the index: angularity, calving interval, non-return rate at 56 days, days to first service, and 305 day first parity lactation. In addition, two production traits not included in the aggregate fertility index were analysed: fat yield and protein yield. Analyses were carried out using all SNPs treated separately, further the most significant marker on BTA14 associated to milk quality located in the DGAT1 region was treated as fixed effect. Genome wide association analysis identified 61 significant SNPs and 75 significant marker-trait associations. Eight additional SNP associations were detected when SNP located near DGAT1 was included as a fixed effect. As there were no obvious common SNPs between the traits analyzed independently in this study, a network analysis was carried out to identify unforeseen relationships that may link production and fertility traits.     

A simple method for genomic selection of moderately sized dairy cattle populations

An efficient algorithm for genomic selection of moderately sized populations based on single nucleotide polymorphism chip technology is described. A total of 995 Israeli Holstein bulls with genetic evaluations based on daughter records were genotyped for either the BovineSNP50 BeadChip or the BovineSNP50 v2 BeadChip. Milk, fat, protein, somatic cell score, female fertility, milk production persistency and herd-life were analyzed. The 400 markers with the greatest effects on each trait were first selected based on individual analysis of each marker with the genetic evaluations of the bulls as the dependent variable. The effects of all 400 markers were estimated jointly using a 'cow model,' estimated from the data truncated to exclude lactations with freshening dates after September 2006. Genotype probabilities for each locus were computed for all animals with missing genotypes. In Method I, genetic evaluations were computed by analysis of the truncated data set with the sum of the marker effects subtracted from each record. Genomic estimated breeding values for the young bulls with genotypes, but without daughter records, were then computed as their parent averages combined with the sum of each animal's marker effects. Method II genomic breeding values were computed based on regressions of estimated breeding values of bulls with daughter record on their parent averages, sum of marker effects and birth year. Method II correlations of the current breeding values of young bulls without daughter records in the truncated data set were higher than the correlations of the current breeding values with the parent averages for fat and protein production, persistency and herd-life. Bias of evaluations, estimated as a difference between the mean of current breeding values of the young bulls and their genomic evaluations, was reduced for milk production traits, persistency and herd-life. Bias for milk production traits was slightly negative, as opposed to the positive bias of parent averages. Correlations of Method II with the means of daughter records adjusted for fixed effects were higher than parent averages for fat, protein, fertility, persistency and herd-life. Reducing the number of markers included in the analysis from 400 to 300 did not reduce correlations of genomic breeding values for protein with current breeding values, but did slightly reduce correlations with means of daughter records. Method II has the advantages as compared with the method of VanRaden in that genotypes of cows can be readily incorporated into the Method II analysis, and it is more effective for moderately sized populations.     

Predictive ability of selected subsets of single nucleotide polymorphisms (SNPs) in a moderately sized dairy cattle population

Several studies have shown that computation of genomic estimated breeding values (GEBV) with accuracies significantly greater than parent average (PA) estimated breeding values (EBVs) requires genotyping of at least several thousand progeny-tested bulls. For all published analyses, GEBV computed from the selected samples of markers have lower or equal accuracy than GEBV derived on the basis of all valid single nucleotide polymorphisms (SNPs). In the current study, we report on four new methods for selection of markers. Milk, fat, protein, somatic cell score, fertility, persistency, herd life and the Israeli selection index were analyzed. The 972 Israeli Holstein bulls genotyped with EBV for milk production traits computed from daughter records in 2012 were assigned into a training set of 844 bulls with progeny test EBV in 2008, and a validation set of 128 young bulls. Numbers of bulls in the two sets varied slightly among the nonproduction traits. In EFF₁₂, SNPs were first selected for each trait based on the effects of each marker on the bulls’ 2012 EBV corrected for effective relationships, as determined by the SNP matrix. EFF₀₈ was the same as EFF₁₂, except that the SNPs were selected on the basis of the 2008 EBV. In DIF_max, the SNPs with the greatest differences in allelic frequency between the bulls in the training and validation sets were selected, whereas in DIF_min the SNPs with the smallest differences were selected. For all methods, the numbers of SNPs retained varied over the range of 300 to 6000. For each trait, except fertility, an optimum number of markers between 800 and 5000 was obtained for EFF₁₂, based on the correlation between the GEBV and current EBV of the validation bulls. For all traits, the difference between the correlation of GEBV and current EBV and the correlation of the PA and current EBV was >0.25. EFF₀₈ was inferior to EFF₁₂, and was generally no better than PA EBV. DIF_max always outperformed DIF_min and generally outperformed EFF₀₈ and PA. Furthermore, GEBV based on DIF_max were generally less biased than PA. It is likely that other methods of SNP selection could improve upon these results.     

Effect of leptin gene polymorphism on the breeding value of milk production traits in Iranian Holstein

New molecular techniques focused on genome analysis, open new possibilities for more accurate evaluation of economiclly important traits in farm animals. Milk production traits are typical quantitative characteristics controlled by a number of genes. Mutations in their sequences may alter animal performance as well as their breeding values. In this study, we investigated the effect of Kpn2I restriction fragment length polymorphisms in the leptin gene, on bull breeding values for milk yield, fat, and protein yield, and their percentage. In order to test for an association between the leptin single-nucleotide polymorphism in exon 2 and milk productivity, we genotyped 134 Iranian Holstein bulls. Breeding values for milk-related traits (milk yield, fat, and protein yield and percentage) were estimated using the BLUP based on an animal model. The effect of the genotypes of Kpn2I polymorphism on the breeding values for milk-related traits was examined using least square methods. The T allele frequency was 0.425. Genotypes were distributed according to the Hardy-Weinberg equilibrium. Bulls with TT genotype had higher milk, fat and protein yield compared with TC and CC bulls (P < 0.05). Bulls with CC genotype had higher protein percentage compared with TT and TC bulls (P < 0.05). The association between leptin polymorphism with milk production traits suggests that this marker may be useful for selection based on molecular information.     

Genome‐wide association study to identify genomic regions affecting prolificacy in Lori‐Bakhtiari sheep

Several causative mutations in candidate genes affecting prolificacy have been detected in various sheep breeds. A genome‐wide association study was performed on estimated breeding values for litter size in Lori‐Bakhtiari sheep. Prolific ewes with twinning records and others with only singleton records were genotyped using the medium‐density Illumina Ovine SNP50 array. Four single nucleotide polymorphisms (SNPs) associated with litter size were identified on chromosomes 3, 6 and 22. The region on sheep chromosome 3 between 75 739 167 and 75 745 152 bp included two significant SNPs (s52383.1 and OAR3_80038014_X.1) in high linkage disequilibrium with each other. The region that surrounds these SNPs contains a novel putative candidate gene: luteinizing hormone/choriogonadotropin receptor (LHCGR), known to be involved in ovarian steroidogenesis and organism‐specific biosystem pathways in sheep. Known prolificacy genes BMPR1B, BMP15 and GDF9 were not associated with litter size in Lori‐Bakhtiari sheep, suggesting that other biological mechanisms could be responsible for the trait's variation in this breed.     

Paternity validation and estimation of genotyping error rate for the BovineSNP50 BeadChip

Incorrect paternity assignment in cattle can have a major effect on rates of genetic gain. Of the 576 Israeli Holstein bulls genotyped by the BovineSNP50 BeadChip, there were 204 bulls for which the father was also genotyped. The results of 38 828 valid single nucleotide polymorphisms (SNPs) were used to validate paternity, determine the genotyping error rates and determine criteria enabling deletion of defective SNPs from further analysis. Based on the criterion of >2% conflicts between the genotype of the putative sire and son, paternity was rejected for seven bulls (3.5%). The remaining bulls had fewer conflicts by one or two orders of magnitude. Excluding these seven bulls, all other discrepancies between sire and son genotypes are assumed to be caused by genotyping mistakes. The frequency of discrepancies was >0.07 for nine SNPs, and >0.025 for 81 SNPs. The overall frequency of discrepancies was reduced from 0.00017 to 0.00010 after deletion of these 81 SNPs, and the total expected fraction of genotyping errors was estimated to be 0.05%. Paternity of bulls that are genotyped for genomic selection may be verified or traced against candidate sires at virtually no additional cost.     

Reliabilities of genomic estimated breeding values in Danish Jersey

In order to optimize the use of genomic selection in breeding plans, it is essential to have reliable estimates of the genomic breeding values. This study investigated reliabilities of direct genomic values (DGVs) in the Jersey population estimated by three different methods. The validation methods were (i) fivefold cross-validation and (ii) validation on the most recent 3 years of bulls. The reliability of DGV was assessed using squared correlations between DGV and deregressed proofs (DRPs). In the recent 3-year validation model, estimated reliabilities were also used to assess the reliabilities of DGV. The data set consisted of 1003 Danish Jersey bulls with conventional estimated breeding values (EBVs) for 14 different traits included in the Nordic selection index. The bulls were genotyped for Single-nucleotide polymorphism (SNP) markers using the Illumina 54 K chip. A Bayesian method was used to estimate the SNP marker effects. The corrected squared correlations between DGV and DRP were on average across all traits 0.04 higher than the squared correlation between DRP and the pedigree index. This shows that there is a gain in accuracy due to incorporation of marker information compared with parent index pre-selection only. Averaged across traits, the estimates of reliability of DGVs ranged from 0.20 for validation on the most recent 3 years of bulls and up to 0.42 for expected reliabilities. Reliabilities from the cross-validation were on average 0.24. For the individual traits, the reliability varied from 0.12 (direct birth) to 0.39 (milk). Bulls whose sires were included in the reference group had an average reliability of 0.25, whereas the bulls whose sires were not included in the reference group had an average reliability that was 0.05 lower.     

Effects of <Emphasis Type="Italic">Mbo</Emphasis>II and <Emphasis Type="Italic">BspM</Emphasis>I polymorphisms in the gonadotropin releasing hormone receptor (<Emphasis Type="Italic">GnRHR</Emphasis>) gene on sperm quality in Holstein bulls

The hypothalamic gonadotropin-releasing hormone receptor (GnRHR) plays an essential physiological role in reproductive function, which triggers the synthesis and release of luteinizing hormone and follicle stimulating hormone in the pituitary. The objective of this study was to investigate the effects of polymorphisms of GnRHR gene on the quality of fresh and frozen semen in Holstein bulls. The PCR-RFLP method was applied to detect G286A and T340C transitions determining MboII and BspMI polymorphisms, respectively, in the exon I of bovine GnRHR gene and evaluated its associations with sperm quality traits in 131 Holstein bulls. In polymorphic locus 286, bulls with the GA genotype had significantly higher sperm motility in frozen semen (FMOT) than GG genotype (P < 0.01). In polymorphic locus 340, bulls with heterozygote CT genotype had significantly higher sperm motility (MOT), semen volume per ejaculate (VOL), and lower abnormal spermatozoa rate (ASR) than homozygote TT genotype (P < 0.05). Bulls contained one A allele or C allele had a favorable, positive effect on sperm quality traits. These results indicate that GnRHR gene can be a potential marker for improving sperm quality traits, and imply that bulls with GA or CT genotype should be selected in breeding program.     

Exploration of relationships between production and fertility traits in dairy cattle via association studies of SNPs within candidate genes derived by expression profiling

The objective of this work was to integrate findings from functional genomics studies with genome-wide association studies for fertility and production traits in dairy cattle. Association analyses of production and fertility traits with SNPs located within or close to 170 candidate genes derived from two gene expression studies and from the literature were performed. Data from 2294 Holstein bulls genotyped for 39557 SNPs were used. A total of 111 SNPs were located on chromosomal segments covered by a candidate gene. Allele substitution effects for each SNP were estimated using a mixed model with a fixed effect of marker and a random polygenic effect. Assumed covariance was derived either from marker or from pedigree information. Results from the analysis with the kinship matrix built from marker genotypes were more conservative than from the analysis with the pedigree-derived relationship matrix. From sixteen SNPs with significant effects on both classes of traits, ten provided evidence of an antagonistic relationship between productivity and fertility. However, we found four SNPs with favourable effects on fertility and on yield traits, one SNP with favourable effects on fertility and percentage traits, and one SNP with antagonistic effects on two fertility traits. While most quantitative genetic studies have proven genetic antagonisms between yield and functional traits, improvements in both production and functionality may be possible when focusing on a few relevant SNPs. Investigations combining input from quantitative genetics and functional genomics with association analysis may be applied for the identification of such SNPs.     

Genetic polymorphisms of the bovine Fatty acid binding protein 4 gene are significantly associated with marbling and carcass weight in Hanwoo (Korean Cattle)

The objective of this study was to investigate an association between polymorphisms in the FABP4 gene and phenotypic variation for marbling and carcass weight (CWT) in a population of Hanwoo steers. We re‐sequenced 4.3 kb of the FABP4 gene region in 24 Hanwoo bulls and identified 16 SNPs and 1 microsatellite polymorphism. Of these 16 SNPs, three SNPs [g.2774G>C (intron I), g.3473A>T (intron II) and g.3631G>A (exon III, creating a p.Met >Val amino acid substitution)] were genotyped in 583 steers to assess their association with carcass traits. The g.3473A allele showed a significant increasing effect on CWT (P = 0.01) and the g.3631G allele was associated with higher marbling score (P = 0.006). One haplotype of these three SNPs (CAG) was significantly associated with CWT (P = 0.02) and marbling score (P = 0.05) and could potentially be of value for marker assisted selection in Hanwoo cattle. The CAG haplotype effect for CWT was larger (11.14 ± 5.03 kg) than the largest single locus effect of g.3473A>T (5.01 ± 2.2 kg).     

Linkage disequilibrium among commonly genotyped SNP variants detected from bull sequence,

Genomic prediction utilizing causal variants could increase selection accuracy above that achieved with SNPs genotyped by currently available arrays used for genomic selection. A number of variants detected from sequencing influential sires are likely to be causal, but noticeable improvements in prediction accuracy using imputed sequence variant genotypes have not been reported. Improvement in accuracy of predicted breeding values may be limited by the accuracy of imputed sequence variants. Using genotypes of SNPs on a high‐density array and non‐synonymous SNPs detected in sequence from influential sires of a multibreed population, results of this examination suggest that linkage disequilibrium between non‐synonymous and array SNPs may be insufficient for accurate imputation from the array to sequence. In contrast to 75% of array SNPs being strongly correlated to another SNP on the array, less than 25% of the non‐synonymous SNPs were strongly correlated to an array SNP. When correlations between non‐synonymous and array SNPs were strong, distances between the SNPs were greater than separation that might be expected based on linkage disequilibrium decay. Consistently near‐perfect whole‐genome linkage disequilibrium between the full array and each non‐synonymous SNP within the sequenced bulls suggests that whole‐genome approaches to infer sequence variants might be more accurate than imputation based on local haplotypes. Opportunity for strong linkage disequilibrium between sequence and array SNPs may be limited by discrepancies in allele frequency distributions, so investigating alternate genotyping approaches and panels providing greater chances of frequency‐matched SNPs strongly correlated to sequence variants is also warranted. Genotypes used for this study are available from https://www.animalgenome.org/repository/pub/ ;USDA2017.0519/.     

Analysis of segregation distortion and association of the bovine FGF2 with fertilization rate and early embryonic survival

Fibroblast growth factor 2 ( FGF2 ) plays an important role in fertility and early embryo development. The objectives of this study were to test the association of FGF2 polymorphisms with fertilization success in cattle using an in vitro fertilization experimental system and to investigate the mechanisms leading to the presence of rare alleles of FGF2 in the Holstein population. A total of 7502 fertilizations were performed and a total of 5049 embryos were produced to collect fertilization and embryo survival records. A total of 444 ovaries, from which oocytes were aspirated and fertilized, were genotyped for two single nucleotide polymorphisms (SNPs) previously identified in FGF2 (g.23G>T and g.11646A>G). Frequency of the TT genotype of the g.23G>T SNP was low in the ovary population (5.4%) and in a different Holstein cattle population (6.6%) examined in this study. Single SNP analysis showed that both SNPs were associated with early embryonic survival rate. Two-way interaction analysis revealed significant association of epistatic interaction between the SNPs with fertilization rate. To test whether or not low frequency of allele T for the g.23G>T SNP in the population is a result of a fertilization failure of T oocytes, semen from six GG bulls was used to fertilize a total of 458 oocytes obtained from 19 GT ovaries. A significant segregation distortion was observed for 169 embryos genotyped for the g.23G>T SNP. We conclude that oocytes carrying the T allele show a reduced fertilization rate and that segregation distortion leads to rarity of the TT genotype in the population.     

Accuracy of marker-assisted selection with single markers and marker haplotypes in cattle

A key question for the implementation of marker-assisted selection (MAS) using markers in linkage disequilibrium with quantitative trait loci (QTLs) is how many markers surrounding each QTL should be used to ensure the marker or marker haplotypes are in sufficient linkage disequilibrium (LD) with the QTL. In this paper we compare the accuracy of MAS using either single markers or marker haplotypes in an Angus cattle data set consisting of 9323 genome-wide single nucleotide polymorphisms (SNPs) genotyped in 379 Angus cattle. The extent of LD in the data set was such that the average marker-marker r2 was 0.2 at 200 kb. The accuracy of MAS increased as the number of markers in the haplotype surrounding the QTL increased, although only when the number of markers in the haplotype was 4 or greater did the accuracy exceed that achieved when the SNP in the highest LD with the QTL was used. A large number of phenotypic records (>1000) were required to accurately estimate the effects of the haplotypes.     

Genetic diversity of the sulfotransferase-like gene and one nonsynonymous SNP associated with growth traits of clam, Meretrix meretrix

The sulfotransferase (SULT) is an important factor in phase II metabolism. Three single nucleotide polymorphisms (SNPs; MmeSUl-696, MmeSUl-714 and MmeSUl-806) were discovered in a SULT-like gene of Meretrix meretrix. A modified allele-specific PCR detection assay was developed to perform polymorphism analysis of the three SNPs in two families and two populations of M. meretrix. Results showed that the genotype of the three SNPs is accordance to the expected Mendelian segregation ratios and conforms to Hardy–Weinberg Equilibrium (HWE) in families and populations, respectively. Moreover, sampled clams (n = 151) from the two populations were tested for the associations between SNPs and growth traits. The single SNP association analysis indicated MmeSUl-806 significantly (P < 0.05) correlated with growth traits of M. meretrix. A further haplotype-trait association analysis confirmed that the three SNPs were in linkage disequilibrium and showed that the haplotype TTG and TCG associated with low growth in the two populations, respectively, which supported that MmeSUl-806 was a growth related marker. This study suggested SULT gene might be a candidate gene related to growth in bivalves and MmeSUl-806 could be a gene marker in linkage map construction and breeding programs of M. meretrix.     

Genome‐wide association study for semen traits of the bulls in Chinese Holstein

A genome‐wide association study (GWAS) was performed to identify markers and candidate genes for five semen traits in the Holstein bull population in China. The analyzed dataset consisted of records from 692 bulls from eight bull stations; each bull was genotyped using the Illumina BovineSNP50 BeadChip. Association tests between each trait and the 41 188 informative high‐quality SNPs were achieved with gapit software. In total, 19 suggestive significant SNPs, partly located within the reported QTL regions or within or close to the reported candidate genes, associated with five semen traits were detected. By combining our GWAS results with the biological functions of these genes, eight novel promising candidate genes, including ETNK1, PDE3A, PDGFRB, CSF1R, WT1, DSCAML1, SOD1 and RUNX2, were identified that potentially relate to semen traits. Our findings may provide a basis for further research on the genetic mechanism of semen traits and marker‐assisted selection of such traits in Holstein bulls.     

Genome‐wide association analysis for growth,muscularity and meat quality in Piétrain pigs

Improvement in growth and meat quality is one of the main objectives in sire line pig breeding programmes. Mapping quantitative trait loci for these traits using experimental crosses and a linkage‐based approach has been performed frequently in the past. The Piétrain breed often was involved as a founder breed to establish the experimental crosses. This breed was selected for muscularity and leanness but shows relatively poor meat quality. It is frequently used as a sire line breed. With the advent of genome‐wide and dense SNP chips in pig genomic research, it is possible to also conduct genome‐wide association studies within the Piétrain breed. In this study, around 500 progeny‐tested sires were genotyped with 60k SNPs. Data filtering showed that around 48k SNPs were useable in this sample. These SNPs were used to conduct a genome‐wide association study for growth, muscularity and meat quality traits. Because it is known that a mutation in the RYR1 gene located on chromosome 6 shows a major effect on meat quality, this mutation was included in the models. Single‐marker and multimarker association analyses were performed. The results revealed between zero and eight significant associations per trait with P < 5 × 10^?5. Of special interest are SNPs located on SSC6, SSC10 and SSC15.